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Ultrasound images of muscle fascicles have been widely used to investigate muscle properties under static/dynamic and pathologic conditions. Fascicle images are usually detected and measured manually, which is subjective and time consuming, especially when dealing with large number of images. In this study, an automatic linear extraction method based on localized Radon transform and revoting strategy is proposed to detect and track muscle fascicles in ultrasound images. The performance of the proposed method is compared to another automatic linear feature extraction method of revoting Hough transform using both simulated images generated by Field II and clinical images from two human subjects. The proposed tracking method is further validated using experimental data. Both the simulation and experimental results show that the proposed method is robust in the presence of speckle noise, accurate in terms of orientation and position measurement, and feasible for analyzing clinical data.